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  2. Linear programming - Wikipedia

    en.wikipedia.org/wiki/Linear_programming

    The simplex algorithm and its variants fall in the family of edge-following algorithms, so named because they solve linear programming problems by moving from vertex to vertex along edges of a polytope. This means that their theoretical performance is limited by the maximum number of edges between any two vertices on the LP polytope.

  3. Cutting-plane method - Wikipedia

    en.wikipedia.org/wiki/Cutting-plane_method

    Cutting planes were proposed by Ralph Gomory in the 1950s as a method for solving integer programming and mixed-integer programming problems. However, most experts, including Gomory himself, considered them to be impractical due to numerical instability, as well as ineffective because many rounds of cuts were needed to make progress towards the solution.

  4. List of two-dimensional geometric shapes - Wikipedia

    en.wikipedia.org/wiki/List_of_two-dimensional...

    This is a list of two-dimensional geometric shapes in Euclidean and other geometries. For mathematical objects in more dimensions, see list of mathematical shapes. For a broader scope, see list of shapes.

  5. Assignment problem - Wikipedia

    en.wikipedia.org/wiki/Assignment_problem

    One way to solve it is to invent a fourth dummy task, perhaps called "sitting still doing nothing", with a cost of 0 for the taxi assigned to it. This reduces the problem to a balanced assignment problem, which can then be solved in the usual way and still give the best solution to the problem.

  6. Basic feasible solution - Wikipedia

    en.wikipedia.org/wiki/Basic_feasible_solution

    For the definitions below, we first present the linear program in the so-called equational form: . maximize subject to = and . where: and are vectors of size n (the number of variables);

  7. Convex hull algorithms - Wikipedia

    en.wikipedia.org/wiki/Convex_hull_algorithms

    Find the two points with the lowest and highest x-coordinates, and the two points with the lowest and highest y-coordinates. (Each of these operations takes O ( n ).) These four points form a convex quadrilateral , and all points that lie in this quadrilateral (except for the four initially chosen vertices) are not part of the convex hull.

  8. Finite volume method for two dimensional diffusion problem

    en.wikipedia.org/wiki/Finite_volume_method_for...

    A portion of the two dimensional grid used for Discretization is shown below: Graph of 2 dimensional plot. In addition to the east (E) and west (W) neighbors, a general grid node P, now also has north (N) and south (S) neighbors. The same notation is used here for all faces and cell dimensions as in one dimensional analysis.

  9. Problem of Apollonius - Wikipedia

    en.wikipedia.org/wiki/Problem_of_Apollonius

    Viète began by solving the PPP case (three points) following the method of Euclid in his Elements. From this, he derived a lemma corresponding to the power of a point theorem, which he used to solve the LPP case (a line and two points). Following Euclid a second time, Viète solved the LLL case (three lines) using the angle bisectors.

  1. Related searches solve the following lpp graphically by means of two dimensional shapes for 5th graders video

    2 dimensional shapes list2 dimensional geometric shapes list